A Proposal Phishing Attack Detection System on Twitter

kamel Ahsene Djaballah, Kamel Boukhalfa, Mohamed Amine Guelmaoui, Amir Saidani and Yassine Ramdane
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kamel Ahsene Djaballah: University of Science and Technology Houari Boumediene, Algiers, Algeria
Kamel Boukhalfa: University of Sciences and Technology Houari Boumediene, Algiers, Algeria
Mohamed Amine Guelmaoui: University of Science and Technology Houari Boumediene, Algiers, Algeria
Amir Saidani: University of Science and Technology Houari Boumediene, Algiers, Algeria
Yassine Ramdane: ERIC Laboratory EA 3083, University of Lyon 2, Lyon, France

International Journal of Information Security and Privacy (IJISP), 2022, vol. 16, issue 1, 1-27

Abstract: The security of personal data is crucial for a company or any individual. Phishing is one of the most common and dangerous cybercrime attacks. These attacks aim to steal information used by individuals and organizations using social engineering, which is a key point for the success of the phishing attack. Even though there are several systems and solutions, the amount of personal information stolen continues to increase as cyberattacks become more difficult to detect. This paper consists of a broad review to study the work carried out in the fight against phishing and the identification of vulnerabilities in existing systems to achieve better efficiency. The authors focused on the social medium Twitter to study the phishing attacks passing through this medium, and they present their new design, which is based on new features. The classification of the approach includes 23 features and uses the MLP artificial neural network (ANN MLP) algorithm. Experiments show that the system is effective at detecting phishing sites, with a 96% success rate using recent data.

Date: 2022
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